Assign sequential count for numerical runs

问题:

I'd like to assign a cumulative numerical value for sequential runs in a binary vector. What I have is

x = [0 0 0 1 1 0 1 1 1 0 1 0 0 0 0 0 0],

and what I would like is

y = [1 2 3 1 2 1 1 2 3 1 1 1 2 3 4 5 6].

The solution using sum/cumsum/unique/find range of functions alludes me. Any help would be greatly appreciated.

回答1:

Here's a way:

a = arrayfun(@(x)(1:x), diff(find([1,diff(x),1])), 'uni', 0);
[a{:}]

The idea is to generate a list of the 'run lengths', i.e. [3,2,1,3,1,1,6] in your case, then just concatenate a bunch of vectors that count to each value in that list, i.e. cat(2, 1:3, 1:2, 1:1, 1:3.... I use arrayfun as a shortcut for reapplying the : operator and then use the comma separated list that {:} returns as a shortcut for the concatenation.

回答2:

(Not a one-liner, alas ...):

F = find(diff(x))+1;
y = ones(size(x));
y(F) = y(F)-diff([1,F]);
y = cumsum(y);

First, find all positions in x where there is a change; then build a vector of 1 where you substract the length of each continuous segment. At the end, take the cumsum of it.

回答3:

Create a sparse matrix such that each run is on a different column, and then do the cumulative sum:

t = sparse(1:numel(x), cumsum([1 diff(x)~=0]), 1);
y = nonzeros(cumsum(t).*t).';

---

Use accumarray with a custom function to generate each increasing pattern in a different cell, and then concatenate all cells:

y = accumarray(cumsum([1 diff(x)~=0]).', 1, [], @(x) {1:numel(x).'});
y = [y{:}];